My personal directory of skills.

Enterprise-grade AI Agent Skills for software development, DevOps, SRE, security, and product teams. Compatible with Claude Code, Cursor, Windsurf, Gemini CLI, GitHub Copilot, and 30+ AI coding agents.

The harness layer for Claude Code — a reference implementation of harness engineering with hook-enforced dual review, state-machine gates that survive context compaction, and fail-closed safety where it counts. Quality gates that AI can't skip.

Professional context and harness engineering for Claude Code and OpenAI Codex. Build production-grade software with spec-driven development, TDD, persistent memory, quality gates, code intelligence, human oversight, and end-to-end verification.

Portable Agent Skill for repository-native Spec programming, informed by public DeepSeek Harness engineering patterns.

A meta-skill that designs domain-specific agent teams, defines specialized agents, and generates the skills they use.

Comet: agent skill harness for turning ideas into evaluated workflows

A kit for building with AI agents and also the engineering patterns around it.

Multi-Agent Harness for Production AI

A lightweight agent harness you bolt onto your app so an LLM can operate it — safely, and cheaply.

Turn any repo into an agent-ready workspace for Claude Code, Codex, Cursor, and other coding agents.

The Loop Engine for Claude Code — engineer the loop, not the prompt. 1 router · 9 agents · 16 skills · 4 workflows. Fail-closed gates, test honesty, anti-anchored review.

A local multi-agent harness that works with your existing Claude Code, Codex subscriptions, allows you to run an office of agents

HAR: open agent harness (CLI + MCP) for coding agents. Isolated worktrees, deterministic verify, software factory workflows for Claude Code, Cursor, and Codex.

The first AI plugin that speaks first. Code-enforced learning + active forgetting + PAC (Proactive Accountability Challenge). Works with Claude Code, Gemini CLI, Hermes, OpenClaw.

Local-first, self-hosted AI agent runtime and MCP bridge with sandboxed sessions, memory, credentials, audit/replay, and a local Console.

MCP Toolkit for Flutter AI Agent Driven Development (MCP/CLI + custom client side tools) - via closed feedback loop (visual & semantic snapshot) and high client side customization adaptable for any Flutter app. Nowadays it is often called as agentic harness.

Cut AI context cost without trusting the compressor. Every reduction is reversible, byte-exact recoverable, and carries an auditable receipt. Local-first, works through proxy, MCP, SDK, or agent wrapper.

AI coding agent with one Python core and three front-ends — headless CLI, Textual TUI, and an Electron desktop. Works with any OpenAI-compatible API, with risk-tiered permissions, event-sourced replayable sessions, and a fail-closed OS-level sandbox.

Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce — the server blocks the call if they don't. Works with any MCP-compatible client.